opencv/modules/gpu/src/constantspacebp_gpu.cpp

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#include "precomp.hpp"

using namespace cv;
using namespace cv::gpu;
using namespace std;

#if !defined (HAVE_CUDA)

void cv::gpu::StereoConstantSpaceBP::estimateRecommendedParams(int, int, int&, int&, int&, int&) { throw_nogpu(); }

cv::gpu::StereoConstantSpaceBP::StereoConstantSpaceBP(int, int, int, int, int) { throw_nogpu(); }
cv::gpu::StereoConstantSpaceBP::StereoConstantSpaceBP(int, int, int, int, float, float, float, float, int, int) { throw_nogpu(); }

void cv::gpu::StereoConstantSpaceBP::operator()(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
void cv::gpu::StereoConstantSpaceBP::operator()(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }

#else /* !defined (HAVE_CUDA) */

namespace cv { namespace gpu { namespace csbp
{
    void load_constants(int ndisp, float max_data_term, float data_weight, float max_disc_term, float disc_single_jump, int min_disp_th,
        const DevMem2D& left, const DevMem2D& right, const DevMem2D& temp);

    void init_data_cost(int rows, int cols, short* disp_selected_pyr, short* data_cost_selected,
        size_t msg_step, int h, int w, int level, int nr_plane, int ndisp, int channels, bool use_local_init_data_cost, cudaStream_t stream);

    void init_data_cost(int rows, int cols, float* disp_selected_pyr, float* data_cost_selected,
        size_t msg_step, int h, int w, int level, int nr_plane, int ndisp, int channels, bool use_local_init_data_cost, cudaStream_t stream);

    void compute_data_cost(const short* disp_selected_pyr, short* data_cost, size_t msg_step1, size_t msg_step2,
        int rows, int cols, int h, int w, int h2, int level, int nr_plane, int channels, cudaStream_t stream);
    void compute_data_cost(const float* disp_selected_pyr, float* data_cost, size_t msg_step1, size_t msg_step2,
        int rows, int cols, int h, int w, int h2, int level, int nr_plane, int channels, cudaStream_t stream);

    void init_message(short* u_new, short* d_new, short* l_new, short* r_new,
        const short* u_cur, const short* d_cur, const short* l_cur, const short* r_cur,
        short* selected_disp_pyr_new, const short* selected_disp_pyr_cur,
        short* data_cost_selected, const short* data_cost, size_t msg_step1, size_t msg_step2,
        int h, int w, int nr_plane, int h2, int w2, int nr_plane2, cudaStream_t stream);

    void init_message(float* u_new, float* d_new, float* l_new, float* r_new,
        const float* u_cur, const float* d_cur, const float* l_cur, const float* r_cur,
        float* selected_disp_pyr_new, const float* selected_disp_pyr_cur,
        float* data_cost_selected, const float* data_cost, size_t msg_step1, size_t msg_step2,
        int h, int w, int nr_plane, int h2, int w2, int nr_plane2, cudaStream_t stream);

    void calc_all_iterations(short* u, short* d, short* l, short* r, short* data_cost_selected,
        const short* selected_disp_pyr_cur, size_t msg_step, int h, int w, int nr_plane, int iters, cudaStream_t stream);

    void calc_all_iterations(float*u, float* d, float* l, float* r, float* data_cost_selected,
        const float* selected_disp_pyr_cur, size_t msg_step, int h, int w, int nr_plane, int iters, cudaStream_t stream);

    void compute_disp(const short* u, const short* d, const short* l, const short* r, const short* data_cost_selected, const short* disp_selected, size_t msg_step,
        DevMem2D_<short> disp, int nr_plane, cudaStream_t stream);

    void compute_disp(const float* u, const float* d, const float* l, const float* r, const float* data_cost_selected, const float* disp_selected, size_t msg_step,
        DevMem2D_<short> disp, int nr_plane, cudaStream_t stream);
}}}

namespace
{
    const float DEFAULT_MAX_DATA_TERM = 30.0f;
    const float DEFAULT_DATA_WEIGHT = 1.0f;
    const float DEFAULT_MAX_DISC_TERM = 160.0f;
    const float DEFAULT_DISC_SINGLE_JUMP = 10.0f;
}

void cv::gpu::StereoConstantSpaceBP::estimateRecommendedParams(int width, int height, int& ndisp, int& iters, int& levels, int& nr_plane)
{
    ndisp = (int) ((float) width / 3.14f);
    if ((ndisp & 1) != 0) 
        ndisp++;

    int mm = ::max(width, height);
    iters = mm / 100 + ((mm > 1200)? - 4 : 4);

    levels = (int)::log(static_cast<double>(mm)) * 2 / 3;
    if (levels == 0) levels++;

    nr_plane = (int) ((float) ndisp / pow(2.0, levels + 1));
}

cv::gpu::StereoConstantSpaceBP::StereoConstantSpaceBP(int ndisp_, int iters_, int levels_, int nr_plane_,
                                                      int msg_type_)

    : ndisp(ndisp_), iters(iters_), levels(levels_), nr_plane(nr_plane_),
      max_data_term(DEFAULT_MAX_DATA_TERM), data_weight(DEFAULT_DATA_WEIGHT),
      max_disc_term(DEFAULT_MAX_DISC_TERM), disc_single_jump(DEFAULT_DISC_SINGLE_JUMP), min_disp_th(0),
      msg_type(msg_type_), use_local_init_data_cost(true)
{
    CV_Assert(msg_type_ == CV_32F || msg_type_ == CV_16S);
}

cv::gpu::StereoConstantSpaceBP::StereoConstantSpaceBP(int ndisp_, int iters_, int levels_, int nr_plane_,
                                                      float max_data_term_, float data_weight_, float max_disc_term_, float disc_single_jump_,
                                                      int min_disp_th_, int msg_type_)
    : ndisp(ndisp_), iters(iters_), levels(levels_), nr_plane(nr_plane_),
      max_data_term(max_data_term_), data_weight(data_weight_),
      max_disc_term(max_disc_term_), disc_single_jump(disc_single_jump_), min_disp_th(min_disp_th_),
      msg_type(msg_type_), use_local_init_data_cost(true)
{
    CV_Assert(msg_type_ == CV_32F || msg_type_ == CV_16S);
}

template<class T>
static void csbp_operator(StereoConstantSpaceBP& rthis, GpuMat u[2], GpuMat d[2], GpuMat l[2], GpuMat r[2],
                          GpuMat disp_selected_pyr[2], GpuMat& data_cost, GpuMat& data_cost_selected,
                          GpuMat& temp, GpuMat& out, const GpuMat& left, const GpuMat& right, GpuMat& disp, cudaStream_t stream)
{
    CV_DbgAssert(0 < rthis.ndisp && 0 < rthis.iters && 0 < rthis.levels && 0 < rthis.nr_plane
        && left.rows == right.rows && left.cols == right.cols && left.type() == right.type());

    CV_Assert(rthis.levels <= 8 && (left.type() == CV_8UC1 || left.type() == CV_8UC3));

    const Scalar zero = Scalar::all(0);

    ////////////////////////////////////////////////////////////////////////////////////////////
    // Init

    int rows = left.rows;
    int cols = left.cols;

    rthis.levels = min(rthis.levels, int(log((double)rthis.ndisp) / log(2.0)));
    int levels = rthis.levels;

    AutoBuffer<int> buf(levels * 4);

    int* cols_pyr = buf;
    int* rows_pyr = cols_pyr + levels;
    int* nr_plane_pyr = rows_pyr + levels;
    int* step_pyr = nr_plane_pyr + levels;

    cols_pyr[0] = cols;
    rows_pyr[0] = rows;
    nr_plane_pyr[0] = rthis.nr_plane;

    const int n = 64;
    step_pyr[0] = alignSize(cols * sizeof(T), n) / sizeof(T);
    for (int i = 1; i < levels; i++)
    {
        cols_pyr[i] = (cols_pyr[i-1] + 1) / 2;
        rows_pyr[i] = (rows_pyr[i-1] + 1) / 2;

        nr_plane_pyr[i] = nr_plane_pyr[i-1] * 2;

        step_pyr[i] = alignSize(cols_pyr[i] * sizeof(T), n) / sizeof(T);
    }

    Size msg_size(step_pyr[0], rows * nr_plane_pyr[0]);
    Size data_cost_size(step_pyr[0], rows * nr_plane_pyr[0] * 2);

    u[0].create(msg_size, DataType<T>::type);
    d[0].create(msg_size, DataType<T>::type);
    l[0].create(msg_size, DataType<T>::type);
    r[0].create(msg_size, DataType<T>::type);

    u[1].create(msg_size, DataType<T>::type);
    d[1].create(msg_size, DataType<T>::type);
    l[1].create(msg_size, DataType<T>::type);
    r[1].create(msg_size, DataType<T>::type);

    disp_selected_pyr[0].create(msg_size, DataType<T>::type);
    disp_selected_pyr[1].create(msg_size, DataType<T>::type);

    data_cost.create(data_cost_size, DataType<T>::type);
    data_cost_selected.create(msg_size, DataType<T>::type);

    step_pyr[0] = data_cost.step / sizeof(T);

    Size temp_size = data_cost_size;
    if (data_cost_size.width * data_cost_size.height < step_pyr[levels - 1] * rows_pyr[levels - 1] * rthis.ndisp)
        temp_size = Size(step_pyr[levels - 1], rows_pyr[levels - 1] * rthis.ndisp);

    temp.create(temp_size, DataType<T>::type);

    ////////////////////////////////////////////////////////////////////////////
    // Compute

    csbp::load_constants(rthis.ndisp, rthis.max_data_term, rthis.data_weight,
        rthis.max_disc_term, rthis.disc_single_jump, rthis.min_disp_th, left, right, temp);

    l[0] = zero;
    d[0] = zero;
    r[0] = zero;
    u[0] = zero;

    l[1] = zero;
    d[1] = zero;
    r[1] = zero;
    u[1] = zero;

    data_cost = zero;
    data_cost_selected = zero;

    int cur_idx = 0;

    for (int i = levels - 1; i >= 0; i--)
    {
        if (i == levels - 1)
        {
            csbp::init_data_cost(left.rows, left.cols, disp_selected_pyr[cur_idx].ptr<T>(), data_cost_selected.ptr<T>(),
                step_pyr[i], rows_pyr[i], cols_pyr[i], i, nr_plane_pyr[i], rthis.ndisp, left.channels(), rthis.use_local_init_data_cost, stream);
        }
        else
        {
            csbp::compute_data_cost(disp_selected_pyr[cur_idx].ptr<T>(), data_cost.ptr<T>(), step_pyr[i], step_pyr[i+1],
                left.rows, left.cols, rows_pyr[i], cols_pyr[i], rows_pyr[i+1], i, nr_plane_pyr[i+1], left.channels(), stream);

            int new_idx = (cur_idx + 1) & 1;

            csbp::init_message(u[new_idx].ptr<T>(), d[new_idx].ptr<T>(), l[new_idx].ptr<T>(), r[new_idx].ptr<T>(),
                               u[cur_idx].ptr<T>(), d[cur_idx].ptr<T>(), l[cur_idx].ptr<T>(), r[cur_idx].ptr<T>(),
                               disp_selected_pyr[new_idx].ptr<T>(), disp_selected_pyr[cur_idx].ptr<T>(),
                               data_cost_selected.ptr<T>(), data_cost.ptr<T>(), step_pyr[i], step_pyr[i+1], rows_pyr[i],
                               cols_pyr[i], nr_plane_pyr[i], rows_pyr[i+1], cols_pyr[i+1], nr_plane_pyr[i+1], stream);

            cur_idx = new_idx;
        }

        csbp::calc_all_iterations(u[cur_idx].ptr<T>(), d[cur_idx].ptr<T>(), l[cur_idx].ptr<T>(), r[cur_idx].ptr<T>(),
                                  data_cost_selected.ptr<T>(), disp_selected_pyr[cur_idx].ptr<T>(), step_pyr[i],
                                  rows_pyr[i], cols_pyr[i], nr_plane_pyr[i], rthis.iters, stream);
    }

    if (disp.empty())
        disp.create(rows, cols, CV_16S);

    out = ((disp.type() == CV_16S) ? disp : (out.create(rows, cols, CV_16S), out));
    out = zero;

    csbp::compute_disp(u[cur_idx].ptr<T>(), d[cur_idx].ptr<T>(), l[cur_idx].ptr<T>(), r[cur_idx].ptr<T>(),
                       data_cost_selected.ptr<T>(), disp_selected_pyr[cur_idx].ptr<T>(), step_pyr[0], out, nr_plane_pyr[0], stream);

    if (disp.type() != CV_16S)
        out.convertTo(disp, disp.type());
}


typedef void (*csbp_operator_t)(StereoConstantSpaceBP& rthis, GpuMat u[2], GpuMat d[2], GpuMat l[2], GpuMat r[2],
                                     GpuMat disp_selected_pyr[2], GpuMat& data_cost, GpuMat& data_cost_selected,
                                     GpuMat& temp, GpuMat& out, const GpuMat& left, const GpuMat& right, GpuMat& disp, cudaStream_t stream);

const static csbp_operator_t operators[] = {0, 0, 0, csbp_operator<short>, 0, csbp_operator<float>, 0, 0};

void cv::gpu::StereoConstantSpaceBP::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp)
{
    CV_Assert(msg_type == CV_32F || msg_type == CV_16S);
    operators[msg_type](*this, u, d, l, r, disp_selected_pyr, data_cost, data_cost_selected, temp, out, left, right, disp, 0);
}

void cv::gpu::StereoConstantSpaceBP::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp, Stream& stream)
{
    CV_Assert(msg_type == CV_32F || msg_type == CV_16S);
    operators[msg_type](*this, u, d, l, r, disp_selected_pyr, data_cost, data_cost_selected, temp, out, left, right, disp, StreamAccessor::getStream(stream));
}

#endif /* !defined (HAVE_CUDA) */